A Modeling Approach for Analyzing the Hydrological Impacts of the Agribusiness Land-Use Scenarios in an Amazon Basin

Author:

Cunha Zandra A.1,Mello Carlos R.23ORCID,Beskow Samuel1ORCID,Vargas Marcelle M.1,Guzman Jorge A.3,Moura Maíra M.1

Affiliation:

1. Water Resources Graduate Program, Federal University of Pelotas de Pelotas (UFPel), Gomes Carneito Street 1, Porto, Pelotas 96010-610, RS, Brazil

2. Water Resources Department, School of Engineering, Federal University of Lavras (UFLA), Lavras 37200-900, MG, Brazil

3. Department of Agricultural and Biological Engineering, College of ACES, University of Illinois at Ubana-Champaign, Urbana, IL 61801, USA

Abstract

The Xingu River Basin (XRB) in the Brazilian Amazon region has a great relevance to the development of northern Brazil because of the Belo Monte hydropower plant and its crescent agribusiness expansion. This study aimed to evaluate the potential of the Lavras Simulation of the Hydrology (LASH) model to represent the main hydrological processes in the XRB and simulate the hydrological impacts in the face of land-use change scenarios. Following the trend of the most relevant agribusiness evolution in the XRB, four agribusiness scenarios (S) were structured considering the increase in grasslands (S1: 50% over the native forest; S2: 100% over the native forest) and soybean plantations (S3: 50% over the native forest; S4: 100% over native forest). Average hydrographs were simulated, and the frequency duration curves (FDC) and average annual values of the main hydrological components for each scenario were compared. The results showed that, in general, changes in land use based on deforestation in the XRB would lead to an increase in flood streamflow and a reduction in baseflow. The increases in direct surface runoff varied from 4.4% for S1 to 29.8% for S4 scenarios. The reduction in baseflow varied from −1.6% for S1 to −4.9% for S2. These changes were reduced when the entire XRB was analyzed, but notable for the sub-basins in its headwater region, where the scenarios were more effective.

Funder

Conselho Nacional de Pesquisa e Desenvolvimento Científico—CNPq

Carlos R. Mello

Publisher

MDPI AG

Subject

Nature and Landscape Conservation,Ecology,Global and Planetary Change

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